Senior R Developer

Civey

Berlin, DE

October 2023 - August 2022

• Developed R statistical libraries used daily to transform millions of user’s poll answers into statistically representative results, used on all the company’s costumer-facing products.
• Analyzed data from millions of users using R, PostgreSQL and Clickhouse and produced visualizations, dashboards and reports to answer stakeholder’s analytical requests, resulting in a better support for decisions across our products.
• Contributed to an extensive refactoring of a core functionality which simplified its maintenance and improved its extendibility, culminating in the development of a new product.
• Coordinated the monitoring of our R software products, including the cooperation with other teams, which resulted in the development of new monitoring features and dashboards (e.g. Slack bots or Redash Dashboards) and in an improved communication and efficiency in problem-solving.
• Developed internal tools with R, Bash, PostgreSQL, Clickhouse and Python used to support other teams, resulting in an increased speed and flexibility to meet customer’s requests.
• Created documentation covering the statistical concepts and logic used in our products, which resulted in the improved understanding of our products, both internally and by other teams.
• Trained new team members by using documentation, learning sessions, joint code reviews and pair-programming.

R Developer

Civey

Berlin, DE

2022 - 2020

• Contributed to the development of R libraries used to calculate more then 10.000 representative survey results daily.
  
• Lead the development of a new feature for geographical survey analysis, resulting in an new product.
• Developed a service that daily updates statistical estimates of the German population using R and Python Airflow, which directly improved the quality of our poll results.
  
• Contributed to the development of bash command line tool used to configure the R environment in production, resulting in efficient and safe workflow for new releases to production.

Doctoral Research Fellow

Humboldt-University

Berlin, DE

2020 - 2016

• Grant by the International Max Planck Research School on the Life Course.
• Worked with large data (millions of observations), using R to program and test automated quality checking and data manipulation routines.
  
• Applied hierarchical Bayesian regression and mixture modeling techniques, using the Stan probabilistic programming language, to account for different aspects of how the data was structured and generated.
• Use of high performance computing clusters and threading in order to provide scalable modeling solutions, reverting in added time to iterate over model building.
• Developed visualizations using ggplot in R to efficiently communicate insights and assess statistical model performance.

PhD in Computational Psychology

Humboldt-University

Berlin

2022 - 2016

• Grant by the International Max Planck Research School on the Life Course.
• Incomplete - did not graduate.

Erasmus Intensive Program in Mathematical Psychology

University of Tartu

Sagadi, Estonia

2014

Masters in Clinical Psychology

University of Lisbon

Lisbon, Portugal

2015 - 2012

For my thesis I developed and deployed an online survey, and self-learned R to implement a non-standard statistical model. All of which resulted in receiving the highest grade with distinction.

BA in Psychological Sciences

University of Lisbon

Lisbon, Portugal

2011 - 2009